Scientific Collaborator

This research position focuses on simulation of building and communal energy systems, thermal energy storage and their integration in district heating networks in an interdisciplinary collaboration of researchers and Swiss industry partners.

**School**: School of Architecture, Design and Civil Engineering

**Your role****:
We offer a time-limited position until end of 2027, with the possibility for extension, as a scientific collaborator with research focus on simulation of building and communal energy systems.
The position is part of the Innosuisse Flagship project “SwissSTES - Swiss Seasonal Thermal Energy Storage Action Plan and Implementation" and other related research projects.

Your work includes the following responsibilities:

- Supporting ongoing research in building and urban energy systems simulation, including seasonal thermal energy storage (STES) and district heating networks
- Performing building energy systems and thermal network simulations
- Thermal energy system optimization, exploring component sizing and control strategies
- Performing spatial, multi-criteria analysis (GIS) for identification of renewable energy and thermal storage potentials
- Data handling and automatization of workflows, categorization/clustering
- Taking over/supporting project lead
- Writing technical/project reports
- Authoring/co-authoring articles in scientific journals
- Supporting the acquisition of research projects / proposal writing

**Your profile****:
We are looking for a widely interested and open-minded person who likes to work in an interdisciplinary team, at the interface between building systems, architecture and construction.
- Master degree in engineering, physics or related fields with knowhow in building/urban energy systems
- A PhD in a related field is recommended
- Good mathematical modelling skills
- Expertise in conducting energy demand simulation at various scales, from individual buildings to the district level, using both top-down and bottom-up approaches
- Experience in processing climate scenarios and weather data from different sources
- Experience in scripting/programming in Python,...
- Experiences with GIS analysis and data-driven methods is desired (understanding of clustering and spatial interpolation algorithms)
- Experiences with district heating systems is a plus
- Fluency in English oral and written, German level B1 and above desired